As a result, any expensive work performed during configuration slows down every invocation.
Even simple commands like `gradle help` and `gradle tasks`.

The next few subsections introduce techniques that can reduce time spent in the configuration phase.

        /* metric description */ "status" /* metric label */);

auto* phase2_bridge_compilation_time = tsl::monitoring::Sampler<1>::New(
    {"/tensorflow/core/tf2xla/api/v1/phase2_compilation_time",
     "The wall-clock time spent on executing graphs in milliseconds.",
     "configuration"},
    // Power of 1.5 with bucket count 45 (> 23 hours)
    {tsl::monitoring::Buckets::Exponential(1, 1.5, 45)});

	// Value being validated
	Value interface{}

	// Schema used for validation of this value. The schema is also used
	// to determine how to correlate the old object.
	Schema Schema

	// Duration spent on ratcheting validation for this object and all of its
	// children.
	Duration *time.Duration

	// Scratch space below, may change during validation

	// it transitions to _Grunning.
	timeToRun timeHistogram

	// idleTime is the total CPU time Ps have "spent" idle.
	//
	// Reset on each GC cycle.
	idleTime atomic.Int64

	// totalMutexWaitTime is the sum of time goroutines have spent in _Gwaiting
	// with a waitreason of the form waitReasonSync{RW,}Mutex{R,}Lock.
	totalMutexWaitTime atomic.Int64

                }
            }
        });

        if (projectLockStatistics.isEnabled()) {
            LOGGER.warn("Time spent waiting on project locks: " + projectLockStatistics.getTotalWaitTimeMillis() + "ms");
        }
    }

    @Override
    public boolean getAllowsParallelExecution() {

		&compbasemetrics.HistogramOpts{
			Namespace:      namespace,
			Subsystem:      subsystem,
			Name:           "request_wait_duration_seconds",
			Help:           "Length of time a request spent waiting in its queue",
			Buckets:        requestDurationSecondsBuckets,
			StabilityLevel: compbasemetrics.BETA,
		},
		[]string{priorityLevel, flowSchema, "execute"},
	)

  fi
}

# TODO(pjh): this test flakily fails on brand-new clusters, not sure why.
# % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
#                                Dload  Upload   Total   Spent    Left  Speed
# 0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
# curl: (6) Could not resolve host:
# command terminated with exit code 6
function test_linux_pod_to_windows_pod {

   * instead.
   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently
   * outperform {@code LinkedList} except in certain rare and specific situations. Unless you have
   * spent a lot of time benchmarking your specific needs, use one of those instead.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated. Instead,

	CoverageData []byte

	// Duration is the time spent minimizing, not including starting or cleaning up.
	Duration time.Duration

	// Count is the number of values tested.
	Count int64
}

// fuzzArgs contains arguments to workerServer.fuzz. The value to fuzz is
// passed in shared memory.
type fuzzArgs struct {
	// Timeout is the time to spend fuzzing, not including starting or
	// cleaning up.

   * instead.
   *
   * <p><b>Performance note:</b> {@link ArrayList} and {@link java.util.ArrayDeque} consistently
   * outperform {@code LinkedList} except in certain rare and specific situations. Unless you have
   * spent a lot of time benchmarking your specific needs, use one of those instead.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated. Instead,